Add Dash mark

doc/_docstrings/objects.Dash.ipynb

@@ -0,0 +1,168 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3227e585-7166-44e7-b0c2-8570e098102d",
+   "metadata": {
+    "tags": [
+     "hide"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "import seaborn.objects as so\n",
+    "from seaborn import load_dataset\n",
+    "penguins = load_dataset(\"penguins\")"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "1b424322-eaa4-45c7-8007-a671ef2afbde",
+   "metadata": {},
+   "source": [
+    "A line segment is drawn for each datapoint, centered on the value along the orientation axis:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fc835356-2dc2-4583-a9f9-c1fe0a6cc9ea",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "p = so.Plot(penguins, \"species\", \"body_mass_g\", color=\"sex\")\n",
+    "p.add(so.Dash())"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "ad9b94de-f19f-4e60-8275-686e749da39c",
+   "metadata": {},
+   "source": [
+    "A number of properties can be mapped or set directly:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6070a665-ab19-43a6-9eba-e206193d9422",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "p.add(so.Dash(alpha=.5), linewidth=\"flipper_length_mm\")"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "2c4a8291-0a84-4e70-a992-756850933791",
+   "metadata": {},
+   "source": [
+    "The mark has a `width` property, which is relative to the spacing between orientation values:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "315327da-421e-46c8-8a1b-8b87355d0439",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "p.add(so.Dash(width=.5))"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "224bf51a-b8d8-4d8e-b0ab-b63ec6788584",
+   "metadata": {},
+   "source": [
+    "When dodged, the width will automatically adapt:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "227e889c-7ce7-49fc-b985-f7746393930e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "p.add(so.Dash(), so.Dodge())"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "aa807f57-5d37-4faa-8fd2-1e5378115f9f",
+   "metadata": {},
+   "source": [
+    "This mark works well to show aggregate values when paired with a strip plot:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5141e0b8-ea1a-4178-adde-21b4bc2e705f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "(\n",
+    "    p\n",
+    "    .add(so.Dash(), so.Agg(), so.Dodge())\n",
+    "    .add(so.Dots(), so.Dodge(), so.Jitter())\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "f2abd4b7-5afb-4661-95f3-b51bfa101273",
+   "metadata": {},
+   "source": [
+    "When both coordinate variables are numeric, you can control the orientation explicitly:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f6d7e236-327f-460f-b12e-46d7444ac348",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "(\n",
+    "    so.Plot(\n",
+    "        penguins[\"body_mass_g\"],\n",
+    "        penguins[\"flipper_length_mm\"].round(-1),\n",
+    "    )\n",
+    "    .add(so.Dash(), orient=\"y\")\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6811d776-93e5-49ce-88a6-14786a67841d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "py310",
+   "language": "python",
+   "name": "py310"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

doc/api.rst

@@ -44,6 +44,7 @@ Mark objects
     Lines
     Path
     Paths
+    Dash
     Range
 
 .. rubric:: Bar marks

doc/whatsnew/v0.12.1.rst

@@ -4,6 +4,8 @@ v0.12.1 (Unreleased)
 
 - |Feature| Added the :class:`objects.Text` mark (:pr:`3051`).
 
+- |Feature| Added the :class:`objects.Dash` mark (:pr:`3074`).
+
 - |Feature| Added the :class:`objects.Perc` stat (:pr:`3063`).
 
 - |Feature| The :class:`Band` and :class:`Range` marks will now cover the full extent of the data if `min` / `max` variables are not explicitly assigned or added in a transform (:pr:`3056`).

seaborn/_marks/line.py

@@ -166,10 +166,9 @@ def __post_init__(self):
         # even when they are dashed. It's a slight inconsistency, but looks fine IMO.
         self.artist_kws.setdefault("capstyle", mpl.rcParams["lines.solid_capstyle"])
 
-    def _setup_lines(self, split_gen, scales, orient):
+    def _plot(self, split_gen, scales, orient):
 
         line_data = {}
-
         for keys, data, ax in split_gen(keep_na=not self._sort):
 
             if ax not in line_data:
@@ -180,24 +179,16 @@ def _setup_lines(self, split_gen, scales, orient):
                     "linestyles": [],
                 }
 
+            segments = self._setup_segments(data, orient)
+            line_data[ax]["segments"].extend(segments)
+            n = len(segments)
+
             vals = resolve_properties(self, keys, scales)
             vals["color"] = resolve_color(self, keys, scales=scales)
 
-            if self._sort:
-                data = data.sort_values(orient, kind="mergesort")
-
-            # Column stack to avoid block consolidation
-            xy = np.column_stack([data["x"], data["y"]])
-            line_data[ax]["segments"].append(xy)
-            line_data[ax]["colors"].append(vals["color"])
-            line_data[ax]["linewidths"].append(vals["linewidth"])
-            line_data[ax]["linestyles"].append(vals["linestyle"])
-
-        return line_data
-
-    def _plot(self, split_gen, scales, orient):
-
-        line_data = self._setup_lines(split_gen, scales, orient)
+            line_data[ax]["colors"].extend([vals["color"]] * n)
+            line_data[ax]["linewidths"].extend([vals["linewidth"]] * n)
+            line_data[ax]["linestyles"].extend([vals["linestyle"]] * n)
 
         for ax, ax_data in line_data.items():
             lines = mpl.collections.LineCollection(**ax_data, **self.artist_kws)
@@ -225,6 +216,16 @@ def _legend_artist(self, variables, value, scales):
             **artist_kws,
         )
 
+    def _setup_segments(self, data, orient):
+
+        if self._sort:
+            data = data.sort_values(orient, kind="mergesort")
+
+        # Column stack to avoid block consolidation
+        xy = np.column_stack([data["x"], data["y"]])
+
+        return [xy]
+
 
 @document_properties
 @dataclass
@@ -255,41 +256,39 @@ class Range(Paths):
     .. include:: ../docstrings/objects.Range.rst
 
     """
-    def _setup_lines(self, split_gen, scales, orient):
-
-        line_data = {}
-
-        other = {"x": "y", "y": "x"}[orient]
+    def _setup_segments(self, data, orient):
 
-        for keys, data, ax in split_gen(keep_na=not self._sort):
+        # TODO better checks on what variables we have
+        # TODO what if only one exist?
+        val = {"x": "y", "y": "x"}[orient]
+        if not set(data.columns) & {f"{val}min", f"{val}max"}:
+            agg = {f"{val}min": (val, "min"), f"{val}max": (val, "max")}
+            data = data.groupby(orient).agg(**agg).reset_index()
 
-            if ax not in line_data:
-                line_data[ax] = {
-                    "segments": [],
-                    "colors": [],
-                    "linewidths": [],
-                    "linestyles": [],
-                }
-
-            # TODO better checks on what variables we have
+        cols = [orient, f"{val}min", f"{val}max"]
+        data = data[cols].melt(orient, value_name=val)[["x", "y"]]
+        segments = [d.to_numpy() for _, d in data.groupby(orient)]
+        return segments
 
-            vals = resolve_properties(self, keys, scales)
-            vals["color"] = resolve_color(self, keys, scales=scales)
 
-            # TODO what if only one exist?
-            if not set(data.columns) & {f"{other}min", f"{other}max"}:
-                agg = {f"{other}min": (other, "min"), f"{other}max": (other, "max")}
-                data = data.groupby(orient).agg(**agg).reset_index()
+@document_properties
+@dataclass
+class Dash(Paths):
+    """
+    A line mark drawn as an oriented segment for each datapoint.
 
-            cols = [orient, f"{other}min", f"{other}max"]
-            data = data[cols].melt(orient, value_name=other)[["x", "y"]]
-            segments = [d.to_numpy() for _, d in data.groupby(orient)]
+    Examples
+    --------
+    .. include:: ../docstrings/objects.Dash.rst
 
-            line_data[ax]["segments"].extend(segments)
+    """
+    width: MappableFloat = Mappable(.8, grouping=False)
 
-            n = len(segments)
-            line_data[ax]["colors"].extend([vals["color"]] * n)
-            line_data[ax]["linewidths"].extend([vals["linewidth"]] * n)
-            line_data[ax]["linestyles"].extend([vals["linestyle"]] * n)
+    def _setup_segments(self, data, orient):
 
-        return line_data
+        ori = ["x", "y"].index(orient)
+        xys = data[["x", "y"]].to_numpy().astype(float)
+        segments = np.stack([xys, xys], axis=1)
+        segments[:, 0, ori] -= data["width"] / 2
+        segments[:, 1, ori] += data["width"] / 2
+        return segments

seaborn/objects.py

@@ -32,7 +32,7 @@
 from seaborn._marks.area import Area, Band  # noqa: F401
 from seaborn._marks.bar import Bar, Bars  # noqa: F401
 from seaborn._marks.dot import Dot, Dots  # noqa: F401
-from seaborn._marks.line import Line, Lines, Path, Paths, Range  # noqa: F401
+from seaborn._marks.line import Dash, Line, Lines, Path, Paths, Range  # noqa: F401
 from seaborn._marks.text import Text  # noqa: F401
 
 from seaborn._stats.base import Stat  # noqa: F401